2024 Summer Internship - Data Planning Intern

Department Summary
Genentech Research & Early Development (gRED) has initiated an exciting journey to bring together and further strengthen our computational talent and capabilities by forming a new, central organization - gRED Computational Sciences (gCS). gCS is on a mission to partner across the organization to realize the potential of data, technology and computational approaches that will revolutionize how targets and therapeutics are discovered and developed, ultimately enabling novel treatments for patients across the world.
The Computational Catalysts group within gCS is a diverse, curious and action-driven team at the intersection of computation, engineering and science with ambition to advance our technical excellence. The focus of the team is on partnering with the informatics and scientific communities to create a computational and data ecosystem that powers scientific discovery and accelerates decision making. We aim to modernize our ability to acquire, store, link, share, find and analyze data across the organization through scalable and integrated solutions that truly make every data point count.
Data planning is a crucial step in data management that ensures FAIR (Findable, Accessible, Interoperable, Reusable) data to maximize its value to our scientific community. We are seeking an intern on our Data Planning team to help us improve our Data Planning processes in collaboration with data curators, data managers, and more.
This internship is on site and is based in South San Francisco, CA.
Key Responsibilities

• Conduct an assessment of our current Data Planning process to highlight pain points and gaps
• Analyze operational data to identify bottlenecks and improvement opportunities
• Validate findings and proposed recommendations via internal team and stakeholder interviews
• Develop methods and tools for on-going monitoring and continuous improvement initiatives

Program Highlights:

• Intensive 3 months, full time (40 hours per week) paid internship. (There is a possibility of an extension past 3 months.)
• Program start dates are May/June, preferably in May.
• The candidate must be able to relocate to the San Francisco Bay Area to work on-site in the South San Francisco, California Genentech Campus.
• A stipend will be provided to help alleviate costs associated with the internship.
• Due to the nature of global meetings, the candidate must be available to participate in early morning meetings (as early as 7am PDT; meetings before 9am may be taken remotely).

Who You Are / How to Apply
Please provide a cover letter to be uploaded as the first page of your resume (in PDF form).
In a maximum of one page, double-spaced, please address the following questions:

• Tell us of a time you improved a process.
• Explain how you see this internship aligning with your personal, educational and/or career goals.

Required Education:

• Must be pursuing a bachelor's or graduate (Master's or PhD) degree in the following areas: Operations Management, Data & Analytics, Engineering, Business, or other related field
• Will have completed at least one year of undergraduate studies and is current enrolled in an accredited college/university

Required Skills and Qualifications:

• Experience analyzing large sets of data
• Experience with data visualization, data analytics, process improvement, or process management.
• Experience with data visualization and reporting

Preferred Qualifications:

• Experience applying process improvement techniques and/or project management skills
• Experience with process mapping tools (e.g. Visio, Lucidchart, etc.) and operations management concepts and metrics (e.g. DMAIC, throughput, cycle time, etc.)
• Excellent communication, collaboration, and interpersonal skills.
• Complements our culture and the standards that guide our daily behavior & decisions: Integrity, Courage, and Passion.

Relocation benefits are not available for this job posting.
The expected salary range for this position based on the primary location of San Francisco, CA is $22 - $50/hr. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.
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